学术博客推荐网络的h度实证——以科学网博客为例

The Empirical Study of h-Degree in Recommendation Network of Academic Blogs ——Taking Science Net.cn Blogs as an Example

【目的】研究h度这一新型带权信息网络分析框架在学术博客推荐网络中的特性。【方法】以科学网博客2013年数据为基础,构建学术博客推荐网络,计算h度等相关参数,并辅以信息可视化进行讨论。【结果】学术博客推荐网络中,高h度节点的产生可由信息源(博主)所持有的学术知识内涵导致,也可因信息源提供话题的兴趣外延引发;h度(hA)与节点带权度(NA)之间存在形如NA=b×hA2的近似函数关系;高h度节点通常成为网络中心部分的局部子群组织者。【局限】h度并非完美指标,后续研究可试用改进型h度进行拓展。【结论】h度可作为学术博客推荐网络分析的测度工具之一,对于此类社群的管理可从高h度节点入手。

[Objective] This paper studies the features of h-degree in recommendation network of academic blogs. [Methods] Based on the datasets of blogs in ScienceNet.cn in 2013, construct the recommendation network of academic blogs, calculate the h-degree and related measures, and enter discussion by information visualization. [Results] In recommendation network of academic blogs, the generation of nodes with high h-degree is not only caused by academic knowledge connotations which are held by the information source （bloggers）, but also because of the interest from topic the information source provided. This paper explores an approximate functional relationship （NA=b×hA2） between h-degree （hA） and node weighted degree （NA）. Nodes with high h-degree typically become the organizer of subgroup in the center of a network. [Limitations] H-degree is not a perfect indicator, and the future studies will expand the improved h-degree. [Conclusions] H-degree can be one of the measurements for recommendation network analysis of academic blogs, and h-degree is also important for community management of this kind community.